The research question
Can a cross-sectional effect survive the realities of listings, delistings and fragmented liquidity?
A digital-asset cross-sectional research design examining the less-liquid tail, with explicit venue, survivorship and execution questions.
The technical work
Universe definition, venue-specific data handling, portfolio construction and execution analysis.
The challenge is to connect the economic idea to a precise, reviewable experiment. Data transformations, the moment of a decision and the interpretation of the resulting return series all belong to that specification.
What to challenge
These are evaluation considerations for this domain, not a checklist presented as already passed.
- Survivorship and listing-age bias
- Venue and token identity
- Liquidity and funding costs
- Out-of-sample universes and risk concentration
The data boundary
Venue-specific price, volume, funding and listing histories with consistent token identifiers.
Descriptions are intentionally high-level. Parameters, execution rules and non-public source data are not published here. Withholding an implementation is different from overstating its evidence.
The interesting question is not whether a backtest looks good. It is what would have to be true for the result to mean something.
For the broader framework, see validation. For the engineering context, see the research stack.